Moving beyond Multiple Regression Analysis and Symmetric Tests to Algorithms and Asymmetric Tests
Abstract
This chapter proposes moving beyond relying on the dominant logic of multiple regression analysis (MRA) toward thinking and using algorithms in advancing and testing theory in accounting, consumer research, finance, management, and marketing. The chapter includes an example of testing an MRA model for fit and predictive validity. The same data used for the MRA is used to conduct a fuzzy-set qualitative comparative analysis (fsQCA). The chapter reviews a number of insights by prominent scholars including Gerd Gigerenzer’s treatise that “Scientists’ tools are not neutral.” Tools impact thinking and theory crafting as well theory testing. The discussion may be helpful for early career scholars unfamiliar with David C. McClelland’s brilliance in data analysis and in introducing business research scholars to fsQCA as an alternative tool for theory development and data analysis.
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Acknowledgements
Acknowledgment
The author gratefully acknowledges permission granted by the publisher, Elsevier, to reuse content appearing in this chapter from Woodside (2013).
Citation
Woodside, A.G. (2016), "Moving beyond Multiple Regression Analysis and Symmetric Tests to Algorithms and Asymmetric Tests", Woodside, A.G. (Ed.) Bad to Good, Emerald Group Publishing Limited, Leeds, pp. 83-111. https://doi.org/10.1108/978-1-78635-334-420161004
Publisher
:Emerald Group Publishing Limited
Copyright © 2016 Emerald Group Publishing Limited